BSR-FL

this is the implementation of work "Byzatine-Robust Privacy-Preserving Federated Learning with Low Overheads"

Our functional encryption code is in file "FE-code"

The result of our paper is the result of "PPFL_defender" method

Name		Name	Last commit message	Last commit date
Latest commit History 14 Commits
FE		FE
Creating		Creating
Dataset		Dataset
Distributing		Distributing
Experiments_CIFAR10_IID.ipynb		Experiments_CIFAR10_IID.ipynb
Experiments_CIFAR10_IID.py		Experiments_CIFAR10_IID.py
Experiments_CIFAR10_MILD_NON_IID.ipynb		Experiments_CIFAR10_MILD_NON_IID.ipynb
Experiments_CIFAR10_MILD_NON_IID.py		Experiments_CIFAR10_MILD_NON_IID.py
Experiments_IMDB_IID.ipynb		Experiments_IMDB_IID.ipynb
Experiments_IMDB_IID.py		Experiments_IMDB_IID.py
Experiments_MNIST_EXTREME_NON_IID.ipynb		Experiments_MNIST_EXTREME_NON_IID.ipynb
Experiments_MNIST_EXTREME_NON_IID.py		Experiments_MNIST_EXTREME_NON_IID.py
Experiments_MNIST_IID.ipynb		Experiments_MNIST_IID.ipynb
Experiments_MNIST_IID.py		Experiments_MNIST_IID.py
FE-code		FE-code
FL-poisoning		FL-poisoning
README.md		README.md
aggregation.py		aggregation.py
datasets.py		datasets.py
environment_federated.py		environment_federated.py
experiment_federated.py		experiment_federated.py